arXiv — cs.AI preprintsInternational21 October 2026
SMART: Semantic Segment Mapping and Assessment of Recognition Transcripts with Contextual Rubrics
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arXiv:2610.27820v1 Announce Type: cross Abstract: Word error rate (WER) assigns equal cost to lexical edits despite their different semantic consequences, while overall semantic scores cannot identify which individual errors alter the intended meaning. We formulate ASR semantic evaluation as context-aware, segment-level consequence assessment and propose Semantic Segment Mapping and Assessment of Recognition Transcripts with Contextual Rubrics (SMART), a framework for traceable semantic evaluation and targeted ASR correction. SMART maps reference-hypothesis discrepancies into coherent segments
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